Triple

T7064038
Position Surface form Disambiguated ID Type / Status
Subject Belgian coastal tram line E164298 entity
Predicate connects P390 FINISHED
Object Blankenberge E638512 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Blankenberge | Statement: [Belgian coastal tram line, connects, Blankenberge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blankenberge
Context triple: [Belgian coastal tram line, connects, Blankenberge]
  • A. Veurne
    Veurne is a historic town in western Belgium known for its well-preserved medieval center and Flemish Renaissance architecture.
  • B. Merelbeke
    Merelbeke is a municipality in East Flanders, Belgium, known in part for hosting Ghent University's Faculty of Veterinary Medicine.
  • C. De Panne chosen
    De Panne is a Belgian seaside resort town on the North Sea coast, known for its beaches, dunes, and as the westernmost point of Belgium.
  • D. Roeselare
    Roeselare is a city in western Belgium known as an economic and commercial center in the province of West Flanders.
  • E. Duinkerke
    Duinkerke is the Dutch name for Dunkirk, a historic port city in northern France known for its pivotal World War II evacuation.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c688796c148190adb2f1596f595f22 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e45e80e08190bb1a79a6026d2cd5 completed March 27, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79c880dc08190813bd9bac580530a completed March 28, 2026, 9:16 a.m.
Created at: March 27, 2026, 2:38 p.m.